Toshiaki Watanabe1, Takashi Kobunai, Takashi Akiyoshi, Keiji Matsuda, Soichiro Ishihara, Keijiro Nozawa. 1. 1Department of Surgical Oncology, The University of Tokyo, Bunkyo-ku, Tokyo, Japan 2Tokushima Research Center, Taiho Pharmaceutical Co., Ltd., Harish, Kawauchi-cho, Tokushima, Japan 3Department of Gastroenterological Surgery, Cancer Institute Hospital, Japanese Foundation for Cancer Research, Koto-ku, Tokyo, Japan 4Department of Surgery, Teikyo University School of Medicine, Itabashi-ku, Tokyo, Japan.
Abstract
BACKGROUND: Patients with rectal cancer exhibit a wide spectrum of responses to chemoradiotherapy. Several gene expression signatures have been reported to predict the response to chemoradiotherapy in rectal cancer, but the lack of practical assays has restricted the clinical use of this technique. OBJECTIVE: We aimed to identify a set of discriminating genes that can be used for the clinical prediction of response to chemoradiotherapy in rectal cancer. DESIGN AND SETTINGS: This study is a retrospective analysis of tumor samples in a single institute. PATIENTS: Sixty-two patients who underwent preoperative chemoradiotherapy were studied. MAIN OUTCOME MEASURES: Gene expression was initially studied in 46 training samples by microarray analysis, and the association between gene expression and response to chemoradiotherapy was evaluated. Quantitative reverse transcriptase polymerase chain reaction was performed to validate the microarray expression levels of the discriminating genes. We developed a gene expression model for the prediction of response to chemoradiotherapy based on the reverse transcriptase polymerase chain reaction findings and validated it by using 16 independent test samples. RESULTS: We identified 24 discriminating probes with expression levels that differed significantly between responders and nonresponders. Among 18 genes identified by Gene Symbol, real-time reverse transcriptase polymerase chain reaction showed significant differences in the expression of 16 genes between responders and nonresponders. We constructed a predictive model by using different sets of these 16 genes, and the highest accuracy rate (89.1%) was obtained by using LRRIQ3, FRMD3, SAMD5, and TMC7. The predictive accuracy rate of this 4-gene signature in the independent set of 16 patients was 81.3%. LIMITATIONS: Validation in a different and large cohort of patients is necessary. CONCLUSIONS: The 4-gene signature identified in this study is closely associated with response to chemoradiotherapy in rectal cancer.
BACKGROUND:Patients with rectal cancer exhibit a wide spectrum of responses to chemoradiotherapy. Several gene expression signatures have been reported to predict the response to chemoradiotherapy in rectal cancer, but the lack of practical assays has restricted the clinical use of this technique. OBJECTIVE: We aimed to identify a set of discriminating genes that can be used for the clinical prediction of response to chemoradiotherapy in rectal cancer. DESIGN AND SETTINGS: This study is a retrospective analysis of tumor samples in a single institute. PATIENTS: Sixty-two patients who underwent preoperative chemoradiotherapy were studied. MAIN OUTCOME MEASURES: Gene expression was initially studied in 46 training samples by microarray analysis, and the association between gene expression and response to chemoradiotherapy was evaluated. Quantitative reverse transcriptase polymerase chain reaction was performed to validate the microarray expression levels of the discriminating genes. We developed a gene expression model for the prediction of response to chemoradiotherapy based on the reverse transcriptase polymerase chain reaction findings and validated it by using 16 independent test samples. RESULTS: We identified 24 discriminating probes with expression levels that differed significantly between responders and nonresponders. Among 18 genes identified by Gene Symbol, real-time reverse transcriptase polymerase chain reaction showed significant differences in the expression of 16 genes between responders and nonresponders. We constructed a predictive model by using different sets of these 16 genes, and the highest accuracy rate (89.1%) was obtained by using LRRIQ3, FRMD3, SAMD5, and TMC7. The predictive accuracy rate of this 4-gene signature in the independent set of 16 patients was 81.3%. LIMITATIONS: Validation in a different and large cohort of patients is necessary. CONCLUSIONS: The 4-gene signature identified in this study is closely associated with response to chemoradiotherapy in rectal cancer.
Authors: Theodore S Hong; Eliezer M Van Allen; Sophia C Kamran; Jochen K Lennerz; Claire A Margolis; David Liu; Brendan Reardon; Stephanie A Wankowicz; Emily E Van Seventer; Adam Tracy; Jennifer Y Wo; Scott L Carter; Henning Willers; Ryan B Corcoran Journal: Clin Cancer Res Date: 2019-06-28 Impact factor: 12.531
Authors: Hyuk Hur; Min Soo Cho; Woong Sub Koom; Joon Seok Lim; Tae Il Kim; Joong Bae Ahn; Hoguen Kim; Nam Kyu Kim Journal: Chin J Cancer Res Date: 2020-04 Impact factor: 5.087